Instructions to use ProbeX/Model-J__DINO__model_idx_0546 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__DINO__model_idx_0546 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0546") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0546") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0546", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c9e25b4328b98339b408bb907397ab1ec977cb599caa36ca85e17fb362a83b5
- Size of remote file:
- 5.37 kB
- SHA256:
- 89e8e5c83e800b0c0ed411f6deb5ca4d3bef00b4109d9ad01b789ec97696103a
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